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Více informací o knize Data Science, Learning by Latent Structures, and Knowledge Discovery

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Anotace knihy

This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data such as structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering, and pattern recognition methods; strategies for modeling complex data and mining large data sets as well as applications of advanced methods in specific domains of practice. Among the disciplines represented in the contributions are Statistics, Psychology, Biology, Information Retrieval and Library Science, Archeology, Banking and Finance, Computer Science, Economics, Engineering, Geography, Geology, Linguistics and Musicology, Marketing, Mathematics, Medical and Health Sciences, Sociology and Educational Sciences.§§This volume with 48 contributions contains the selected and peer-reviewed papers presented during the European Conference on Data Analysis (ECDA 2013) which was jointly held by the German Classification Society (GfKl) and the French speaking Classification Society (SFC). The conference took place in July 2013 at the CCRN Neumünster Abbey, Luxembourg, under the patronage of the Prime Minister of the Grand Duchy of Luxembourg and it was hosted by the University of Luxembourg.§§

Parametry knihy

Zařazení knihy Knihy v angličtině Reference, information & interdisciplinary subjects Research & information: general Research methods: general

• Plný název: Data Science, Learning by Latent Structures, and Knowledge Discovery
• Autor: Berthold Lausen, Sabine Krolak-Schwerdt, Matthias Böhmer
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 560
• EAN: 9783662449820
• ISBN: 366244982X
• ID: 05340866
• Nakladatelství: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
• Hmotnost: 896 g
• Rozměry: 239 × 163 × 32 mm
• Datum vydání: 18. May 2015

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